Autorentext

Professor Pradhan is a globally recognized expert in geospatial analytics and artificial intelligence applications in Earth and environmental sciences. Currently a Distinguished Professor at the University of Technology Sydney (UTS), Australia, he also leads the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS). With a PhD in GIS-based modeling, Prof. Pradhan has over two decades of experience in spatial data science, remote sensing, natural hazard modeling, and environmental monitoring. He has been listed among the world's top 2% scientists by Stanford University and received numerous international awards, including from IEEE and Elsevier. A Fellow of the Royal Geographical Society (FRGS), he also serves on editorial boards of several top-tier journals. His research integrates geospatial AI and deep learning for disaster risk reduction, land use planning, and sustainability.

Prof. Mahesh Kumar Jat holds B.E. in Civil Engineering (Hons.); M. E. (Water Resources Engineering) and Ph.D. (Integrated Water Resource Management) from IIT Roorkee. The major areas of his research are Integrated Water Resources Management; Hydrological modelling; Climate change, Remote Sensing and GIS Applications.Dr. Abhirup Dikshit is a geospatial ecohydrologist using advanced remote sensing tools and machine learning models to monitor vegetation health and function in the face of climate change, land use, and other major disturbance events. He has published more than 30 articles and was awarded the International Research Training Program (IRTP) scholarship funded by the Australian Government under Department of Education and Training to pursue my doctoral studies in Australia.

Klappentext
Spatial Intelligence for Hydrometeorological Hazards in a Changing Climate explores the intersection of advanced machine learning techniques and the intricate challenges posed by shifting hydrometeorological patterns. This comprehensive guide navigates readers through a diverse landscape of topics, ranging from data-driven models for early prediction of floods, landslides, soil erosion, heat waves, droughts, and novel approaches for assessing the impacts of extreme weather events on ecosystems and societies. Through real-world case studies and practical examples, the book demystifies complex algorithms and equips readers with the skills to harness the power of machine learning.

Whether you are a researcher, practitioner, or enthusiast, this book empowers you to leverage cutting-edge technology to address the urgent and evolving threats of a changing climate.

Inhalt

1. Spatial Intelligence in Hydrometeorological hazard context
2. Future hazard scenarios using climate models (CMIP-6)
3. Impact of climate change on landslide types
4. Landslide Modelling in a Changing Climate
5. Landslide Risk
6. Linkage between drought and climate change
7. Analyzing spatio-temporal droughts using next-gen geostationary satellites
8. Drought Forecasting using Advanced Machine Learning Techniques
9. Quantifying soil erosion impacts due to future climate scenario
10. Flood Modelling using Explainable AI models
11. Flood Mitigation Strategies in a Changing Climate
12. Climate Change and Heat Events
13. Flash Droughts
14. Ethical and Societal Implications of Machine Learning in Climate Hazards